A convenience wrapper around the root_numpy library that allows you to load and save pandas DataFrames in the ROOT format used in high energy phyics.
from pandas import DataFrame
from root_pandas import read_root
data = [1, 2, 3]
df = DataFrame({'AAA': data, 'ABA': data, 'ABB': data})
df.to_root('test.root', 'tree')
df_new = read_root('test.root', 'tree', columns=['A{A,B}A'])
# DataFrames are extremely convenient
df_new['answer'] = 42
df_new.to_root('new.root')
# The file contains a tree called 'tree' with the 'AAA', 'ABA' and 'answer' branches
# There is also an 'index' branch that persists the DataFrame's indexThere is also support for working with files that don't fit into memory:
If the chunksize parameter is specified, read_root returns an iterator that yields DataFrames, each containing up to chunksize rows.
for df in read_root('bigfile.root', 'tree', chunksize=100000):
# process df here
df.to_root('finished.root', mode='a')By default, to_root erases the existing contents of the file. Use mode='a' to append.
The package is currently not on PyPI. To install it into your home directory with pip, run
pip install --user git+https://github.com/ibab/root_pandas